Jan Neumann

4.6k citations
131 papers · 3.3k · 1 hit paper · h-index 28

Impact in

Papers in

Jan Neumann

121 papers receiving 3.2k citations

Jan Neumann's Hit Papers

Learning Temporal Regularity in Video Sequences 2016 · 1.0k citations
1.0k0+3+6Years since publication2505007501000

Peers

Jan Neumann
Comparison fields: 5 of 164
  • Computer Vision and Pattern Recognition 939
  • Catalysis 249
  • Rheumatology 448
  • Artificial Intelligence 1.1k
  • Computer Networks and Communications 611
Replace Jun Tang with:
Jun Tang China
Tingting Chen China
Tingting Jiang China
Mingyu Chen China
Xiyang Liu China
Hui Li China
Kelvin Wong Australia
Wei Qian China
Xiaoming Jin China
Kai Pu Jin China
Jan Neumann relative to Jun Tang China Jun Tang's profile →
Citations per field
00.5×5×11.2×
Jun Tang · 1×
Citations per year

Countries citing papers authored by Jan Neumann

Since Specialization
Citations

This map shows the geographic impact of Jan Neumann's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Jan Neumann with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jan Neumann more than expected).

Fields of papers citing papers by Jan Neumann

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jan Neumann. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Jan Neumann. The network helps show where Jan Neumann may publish in the future.

Co-authors

The 25 scholars most cited alongside Jan Neumann, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Jan Neumann Line = papers co-authored together Jan Neumann links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 131 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Learning Temporal Regularity in Video Sequences
Hit paper breakdown →
20161040
2 201688
3 200786
4 201184
5 201881
6 200264
7 201961
8 202160
9 201758
10 201956
11 201856
12 201853
13 202050
14 201850
15 202247
16 200844
17 200743
18 201241
19 200241
20 201938

About Jan Neumann

Jan Neumann is a scholar working on Rheumatology, Computer Vision and Pattern Recognition, Catalysis, Surgery and Media Technology, having authored 131 papers that have together received 3.3k indexed citations. Recurring topics across this work include Osteoarthritis Treatment and Mechanisms (19 papers), Advanced Vision and Imaging (13 papers), Ionic liquids properties and applications (10 papers), Knee injuries and reconstruction techniques (7 papers), Hip disorders and treatments (6 papers), Advanced Image Processing Techniques (6 papers), Image Processing Techniques and Applications (6 papers) and Sarcoma Diagnosis and Treatment (6 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (939 citations), Catalysis (249 citations), Rheumatology (448 citations), Artificial Intelligence (1.1k citations) and Computer Networks and Communications (611 citations). Jan Neumann has collaborated with scholars based in Germany, United States and Switzerland. Frequent co-authors include Larry Steven Davis, Jonghyun Choi, Mahmudul Hasan, Amit K. Roy–Chowdhury, Thomas Marc Link, Yiannis Aloimonos, Alexandra S. Gersing, Gabby B. Joseph, Dietmar Paschek and Ralf Ludwig. Their work appears in journals such as Osteoarthritis and Cartilage, European Radiology, Skeletal Radiology, Journal of Magnetic Resonance Imaging and European Journal of Radiology.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

Explore authors with similar magnitude of impact